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End of training

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  1. README.md +69 -0
  2. config.json +54 -0
  3. model.safetensors +3 -0
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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: Amadeus99/indonesia-election-topic-classification-undersampling-large-2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: final
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # final
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+
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+ This model is a fine-tuned version of [Amadeus99/indonesia-election-topic-classification-undersampling-large-2](https://huggingface.co/Amadeus99/indonesia-election-topic-classification-undersampling-large-2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3415
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+ - F1 macro: 0.6715
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+ - Weighted: 0.7528
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+ - Balanced accuracy: 0.8185
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
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+ | 0.836 | 1.0 | 39 | 1.0747 | 0.5558 | 0.6819 | 0.7094 |
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+ | 0.5943 | 2.0 | 78 | 0.8587 | 0.6173 | 0.7475 | 0.8326 |
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+ | 0.3032 | 3.0 | 117 | 0.6988 | 0.7499 | 0.7999 | 0.8840 |
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+ | 0.1264 | 4.0 | 156 | 0.8485 | 0.7286 | 0.7915 | 0.8797 |
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+ | 0.0819 | 5.0 | 195 | 0.9576 | 0.7197 | 0.7812 | 0.8816 |
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+ | 0.0084 | 6.0 | 234 | 1.0325 | 0.7060 | 0.7874 | 0.8264 |
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+ | 0.037 | 7.0 | 273 | 1.0728 | 0.7098 | 0.7940 | 0.8261 |
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+ | 0.0176 | 8.0 | 312 | 1.0690 | 0.7148 | 0.7961 | 0.8350 |
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+ | 0.011 | 9.0 | 351 | 1.1196 | 0.7133 | 0.7913 | 0.8341 |
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+ | 0.003 | 10.0 | 390 | 1.1165 | 0.7133 | 0.7913 | 0.8341 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "Amadeus99/indonesia-election-topic-classification-undersampling-large-2",
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+ "_num_labels": 5,
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "id2label": {
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+ "0": "Sumber Daya Alam",
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+ "1": "Politik",
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+ "2": "Demografi",
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+ "3": "Pertahanan dan Keamanan",
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+ "4": "Ideologi",
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+ "5": "Ekonomi",
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+ "6": "Sosial Budaya",
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+ "7": "Geografi"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2,
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+ "LABEL_3": 3,
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+ "LABEL_6": 6,
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+ "LABEL_7": 7
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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